Field of the Invention
The present invention relates to an image processing apparatus and an image processing method for reducing noise contained in image data.
Description of the Related Art
Digital still cameras and digital video cameras have come into widespread general use. These digital image capturing devices generate digital image data by converting, into digital signals, light received by a photoelectric conversion element (image capturing element), such as a CCD or a CMOS sensor.
In the process of generating digital image data, noise, such as dark-current noise, thermal noise, and shot noise is generated by the characteristics of the image capturing element and circuit, and contaminates the digital image data. The noise is more noticeable now than before since the image capturing element of recent years is reduced in size, has more pixels, and, therefore, has a super-high pixel pitch. The noise is generated markedly and is a strong factor of image degradation especially in a case, for example, when ISO sensitivity is increased. For this reason, contaminating noise needs to be reduced to obtain a high-quality image.
In a conventionally-known method, noise is reduced by using a low-pass filter that allows only a signal component at or below a noise frequency to pass therethrough. However, this method blurs, not only the noise, but also, the edge, and, therefore, makes it difficult to obtain a high-quality image. Thus, a number of methods have been proposed for reducing noise adaptively by sorting out, in some way, information on the noise and information on the edge.
General adaptive noise reduction reduces noise in the following manner. Specifically, to reduce noise in a target pixel, multiple pixels near the target pixel are selected as reference pixels, and the value of the target pixel is replaced with an appropriate weighted average of the reference pixels.
As one of methods for the adaptive noise reduction, there is proposed a method that achieves noise reduction by defining an area including a target pixel (a target area), obtaining the similarity between the target pixel and its reference pixels in a unit of the area, and using a weighted average according to the similarity (see Japanese Patent Laid-Open Nos. 2007-536662 and 2011-39675).
However, the methods of Japanese Patent Laid-Open Nos. 2007-536662 and 2011-39675 have a problem that an image that has both an area containing many edges, such as buildings, and a smooth area, such as the sky, exhibits different noise reduction effects depending on the areas. This is because the similarity between a target area and reference pixels varies depending on how the target area is determined. For example, setting a small area as the target area so as to achieve a high noise reduction effect in the area containing edges lowers the noise reduction effect for the smooth area. Conversely, setting a large area as the target area so as to achieve a high noise reduction effect in the smooth area lowers the noise reduction effect for the area containing edges.